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Author Chen, Jidong ♦ Meng, Xiaofeng ♦ Guo, Yanyan ♦ Xiao, Zhen
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Road-network Constraint ♦ Spatial Query ♦ Update-efficient Indexing ♦ Dynamic Index ♦ Different Datasets ♦ Spatial Index ♦ Simulation Experiment ♦ Group Neighbor-ing Object ♦ New Application ♦ Efficient Index ♦ Adaptive Unit ♦ Recent Advance ♦ Prediction Method ♦ Movement Bound ♦ Stochastic Traf-fic Behavior ♦ Road Net-works ♦ New Update-efficient Index Method ♦ Road Network ♦ Adap-tive Unit Structure ♦ Wireless Sensor Network ♦ Dynamic Data Struc-ture ♦ Querying Performance ♦ Similar Movement Pattern ♦ Frequent Object Movement
Description Recent advances in wireless sensor networks and positioning technologies have boosted new applications that manage moving objects. In such applications, a dynamic index is often built to expedite evaluation of spatial queries. However, development of efficient indexes is a challenge due to frequent object movement. In this paper, we propose a new update-efficient index method for moving objects in road net-works. We introduce a dynamic data struc-ture, called adaptive unit, to group neighbor-ing objects with similar movement patterns. To reduce updates, an adaptive unit captures the movement bounds of the objects based on a prediction method, which considers the road-network constraints and stochastic traf-fic behavior. A spatial index (e.g., R-tree) for the road network is then built over the adap-tive unit structures. Simulation experiments, carried on two different datasets, show that an adaptive-unit based index is efficient for both updating and querying performance.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2009-01-01
Publisher Institution Proceedings of the 16th International Conference on Scientific and Statistical Database Management, IEEE Computer Society